Abstract 845: Pan-cancer proteogenomic signatures associated with HRD, MSI, APOBEC, and smoking
Authors: Yize Li, Nadezhda V. Terekhanova, Daniel Cui Zhou, Kelly V. Ruggles, Samuel H. Payne, Michael Wendl, David Fenyő, Li Ding
Journal: Cancer Research (2022)

Abstract The increased quality and data availability of large-scale transcriptomic, genomic, and proteomic studies require a pan-cancer integrated proteogenomic approach to define tumor molecular signatures accurately and identify new therapeutic targets. We comprehensively investigate more than 1000 samples across 12 cancer types from the Clinical Proteomics Tumor Analysis Consortium (CPTAC) and the International Cancer Proteogenome Consortium (ICPC). The types are comprised of breast (BR), colorectal (CO), and ovarian (OV) cancers, clear cell renal cell (ccRCC), head and neck squamous cell (HNSCC), lung squamous cell (LSCC), hepatitis B virus (HBV)-related hepatocellular (HCC), and endometrial (EC) carcinomas, lung adenocarcinoma (LUAD), pancreatic ductal adenocarcinoma (PDAC), and glioblastoma (GBM). In particular, we examine 8 Tumor Signature Associated Phenotypes (TSAPs), namely aristolochic acid (AA), aging, microsatellite instability (MSI), homologous recombination deficiency (HRD), POLE, APOBEC, smoking, and ultraviolet (UV) light exposure. This study is the first to report proteomic markers associated with these TSAPs on a pan-cancer level. In addition to genetic alterations and mutational signatures, we utilize multi-omics data of high-resolution proteome, phosphoproteome, acetylome, and gene expression to infer expression signatures of TSAPs by defining the most critical changes in the transcriptome and proteome accompanying the transitions to these TSAPs, especially markers that were uniquely found in proteomic data. We consolidated multi-omic data and calculated the novel quantitative Tumor Signature Associated Phenotypes (TSAPs) score to predict the TSAP status. For example, the use of proteomic markers for MSI-TSAP scoring can improve clinical testing of MSI status. We further study environmental exposure-related tumor proteogenomic signatures, immune proteogenomic signatures, and the association between the immune subtypes and TSAPs. Smoking strongly influences the tumor immune microenvironment and disease prognosis. We show that expression signatures can facilitate the prediction of TSAPs and help to uncover their underlying molecular mechanisms. By connecting these findings with druggable databases, we provide a link to actionable therapies, identify putative TSAP-related targets, and offer novel cues to optimize therapeutic options for patients, such as how additional targeting of genes up-regulated in PARP1 inhibitor-treated HRD tumors may overcome resistance. This will promote the identification not only of unique druggable targets, but also to determine putative novel therapeutic targets using integrated approaches. Citation Format: Yize Li, Nadezhda V. Terekhanova, Daniel Cui Zhou, Kelly V. Ruggles, Samuel H. Payne, Michael Wendl, David Fenyő, Li Ding. Pan-cancer proteogenomic signatures associated with HRD, MSI, APOBEC, and smoking [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 845.